Coarse-to-Fine Registration of Remote Sensing Optical Images Using SIFT and SPSA Optimization

Abstract

Sub-pixel accuracy is the vital requirement of remote sensing optical image registration. For this purpose, a coarse-to-fine registration algorithm is proposed to register the remote sensing optical images. The coarse registration operation is performed by the scale invariant feature transform (SIFT) approach with an outlier removal method. The outliers are removed by the random sample consensus (RANSAC) algorithm. The fine registration process is performed by maximizing the mutual information between the input images using the first-order simultaneous perturbation stochastic approximation (SPSA) along with the second-order SPSA. To verify the effectiveness of the proposed method, experiments are performed using three sets of optical image pairs.